"""
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""

"""
metrics
"""
import os
import atexit
import shutil
from threading import Lock

from prometheus_client import Histogram, Counter

from fastdeploy.metrics.metrics import build_1_2_5_buckets


class WorkMetricsManager(object):
    """Prometheus Metrics Manager handles all metric updates """

    _initialized = False

    def __init__(self):
        """Initializes the Prometheus metrics and starts the HTTP server if not already initialized."""

        if self._initialized:
            return

        self.e2e_request_latency = Histogram(
            'fastdeploy:e2e_request_latency_seconds',
            'End-to-end request latency (from request arrival to final response)',
            buckets=[
                0.3, 0.5, 0.8, 1.0, 1.5, 2.0, 2.5, 5.0, 10.0, 15.0, 20.0, 30.0,
                40.0, 50.0, 60.0, 120.0, 240.0, 480.0, 960.0, 1920.0, 7680.0
            ]
        )
        self.request_params_max_tokens = Histogram(
            name='fastdeploy:request_params_max_tokens',
            documentation='Histogram of max_tokens parameter in request parameters',
            buckets=build_1_2_5_buckets(33792)
        )
        self.prompt_tokens_total = Counter(
            name="fastdeploy:prompt_tokens_total",
            documentation="Total number of prompt tokens processed",
        )
        self.request_prompt_tokens = Histogram(
            name='fastdeploy:request_prompt_tokens',
            documentation='Number of prefill tokens processed.',
            buckets=build_1_2_5_buckets(33792)
        )

        self._initialized = True


work_process_metrics = WorkMetricsManager()
